Study on Alfalfa Water Use Efficiency and Optimal Irrigation Strategy in Agro-Pastoral Ecotone, Northwestern China

Response to Reviewer 2 Comments

1. Summary

Dear Reviewers:

Thank you for taking time out of your busy schedule to review the manuscript. Now we have carefully corrected and replied to the manuscript for this revision. The revision instructions are as follows:

Point 1 Abstract: The abstract is overly detailed and lengthy. It would be more effective to condense it by focusing on the key highlights and main findings of the study.

Response 1: Thank you very much for the reviewer's opinion. We will take this issue very seriously and make serious changes. We think your opinion is valuable, your opinion will be very helpful in improving the quality of our article! The following changes were made:

Dear reviewer, after your comments, the abstract is revised as follows:

Abstract：Agro-pastoral ecotone is an important livestock production area in the north of China, and alfalfa is the main pasture crop in this area. Aiming to address the issues of groundwater overexploitation in the area with water demand, consumption pattern, the irrigation scheduling, water usage efficiency of alfalfa under the subsurface drip irrigation. Alfalfa was used as the re-search object in this study. DSSAT model was used to simulate the soil moisture, yield and other alfalfa grow characteristics during a two-year in situ observation study, and provide information on the best irrigation techniques and the water-use efficiency of alfalfa in the Agro-pastoral ecotone Northwestern China. The results showed that: the ARE, nRMSE and R² values of alfalfa soil water content, leaf area index and yield varied between 3.82% and 5.57%, 4.81% and 8.06%, and 0.86 and 0.93 respectively, and the accuracy of the calibrated and validated parameters was acceptable, and the model could be applied to this study. The water consumption of alfalfa ranged from 395.6 mm to 421.8 mm during the whole year, and the critical water consumption period was the branching stage and the bud stage. During the branching stage and the bud stage, water consumption was 30-31% and 31-33% of the total water consumption and the water consumption intensity averaging 2.97-3.04 mm/d and 4.23-4.97 mm/d. The variations of WUE and IWUE were 11.74-14.39 kg·m^-3 and 7.12-9.31 kg·m^-3. Irrigation increased the water productivity of rain fed alfalfa by 49.48-64.70%, and increased the yield of alfalfa by 17.87-34.72%. With the highest yield as the goal, the recommended irrigation volumes for normal and dry flow years were 200 mm and 240 mm; with the goal of the highest utilization of groundwater resources, the recommended irrigation volumes for normal and dry flow years were 160 mm and 192 mm. The results of this study are expected to provide scientific and technological support for the rational utilization of groundwater and scientific improvement of alfalfa yield in the Agro-pastoral ecotone Northwestern China.

Point 2: Line 49-53: The writing in this section could be improved for better flow and readability. Consider rephrasing to enhance clarity and coherence.

Response 2: Thank you very much for the reviewer's opinion. We will take this issue very seriously and make serious changes. We think your opinion is valuable, your opinion will be very helpful in improving the quality of our article! The following changes were made:

Dear reviewer, lines 49-53 have been revised to improve flow and readability as follows: 

The Yinshanbeilu region in northern China is a typical agro-pastoral ecotone, playing a vital role in cattle and sheep farming. It is also a key area for the production of artificial forage. Alfalfa (Medicago sativa), a perennial leguminous plant, is particu-larly valuable in this region due to its high nutritional content, impressive yield, and resilience. This forage is not only grazing-tolerant but can also be harvested multiple times over the years [1,2,3]. As a result, alfalfa serves as a crucial source of high-quality forage in the Yinshanbeilu region.

Point 3：Line 61-64: The cited literature appears somewhat tangential to the central theme of the paper. Please clarify its relevance or consider replacing it with more directly related references.

Response 3: Thank you very much for the reviewer's opinion. We will take this issue very seriously and make serious changes. We think your opinion is valuable, your opinion will be very helpful in improving the quality of our article! The following changes were made:

Point 3：Line 61-64: The cited literature appears somewhat tangential to the central theme of the paper. Please clarify its relevance or consider replacing it with more directly related references.

Response 3: Thank you very much for the reviewer's opinion. The reference has been replaced as follows:

Ma et al. [8], a field experiment in Northwest China determined that subsurface irrigation at 75% of crop evapotranspiration (ET_C) combined with a nitrogen application rate of 145–190 kg·ha^-1 optimizes alfalfa yield, quality, water, and nitrogen use efficiency, as well as economic benefits.

Point 4：Line 126-128: The description of the sampling frequency is unclear. I recommend rephrasing or elaborating to ensure readers understand the sampling strategy.

Response 4: Thank you very much for the reviewer's opinion. We will take this issue very seriously and make serious changes. We think your opinion is valuable, your opinion will be very helpful in improving the quality of our article! The following changes were made:

The monitoring period lasted from May 1 to September 30, with samples taken on the 1st and 15th of each month, and more frequent sampling during irrigation periods, the additional sampling date is the next day after each irrigation.

Point 5：Methods: The manuscript does not describe how the Leaf Area Index (LAI) data was collected for model calibration. Please include a detailed explanation of the data collection method to enhance transparency and reproducibility.

Response 5: Thank you very much for the reviewer's opinion. We will take this issue very seriously and make serious changes. We think your opinion is valuable, your opinion will be very helpful in improving the quality of our article! The following changes were made:

Soil samples were taken to a depth of 100 cm, and alfalfa growth indicators such as plant height and leaf area were monitored, leaf area index (LAI) data were collected through di-rect field measurements during key growth stages of alfalfa using a portable LAI meter (LAI-2200C, origin and manufacturer: LI-COR, USA) for all treatment plots.

Point 6：Figure 6: The figure's quality needs improvement. The axis labels and numbers are difficult to read. Please enhance the resolution and ensure all text and details are legible.

Response 6: Thank you very much for the reviewer's opinion. We will take this issue very seriously and make serious changes. We think your opinion is valuable, your opinion will be very helpful in improving the quality of our article! The following changes were made:

Figure 3. Growth stages of different crops.

Figure 4. Validation on the soil water content, leaf area, yield of the alfalfa.

Figure 5. Soil water dynamics during the depth of 0–60 cm soil profile. Note: SMC stands for Soil Moisture Content. The dot is the measured value, and the curve is the simulation value.

Figure 6. Leaf area Change trends of alfalfa. Note: LAl- Leaf area index.

Figure 7. Yield change trend of alfalfa.

Figure 8. Rainfall frequency curve.

Figure 9. Rainfall during alfalfa growth stage from 1991 to 2023.

Figure 10. Effects of irrigation schemes on alfalfa yield in different hydrological years.

Response to Reviewer 3 Comments

1. Summary

Dear Reviewers:

Thank you for taking time out of your busy schedule to review the manuscript. Now we have carefully corrected and replied to the manuscript for this revision. The revision instructions are as follows:

Point 1: The abstract contains too much information.l suggest rewriting it to primarily focus on the problem (why), where, how, and briefly include the results and conclusion to improve readability.

Response 1: Thank you very much for the reviewer's opinion. We will take this issue very seriously and make serious changes. We think your opinion is valuable, your opinion will be very helpful in improving the quality of our article! The following changes were made:

Dear reviewer, after your comments, the abstract is revised as follows:

Abstract：Agro-pastoral ecotone is an important livestock production area in the north of China, and alfalfa is the main pasture crop in this area. Aiming to address the issues of groundwater overexploitation in the area with water demand, consumption pattern, the irrigation scheduling, water usage efficiency of alfalfa under the subsurface drip irrigation. Alfalfa was used as the re-search object in this study. DSSAT model was used to simulate the soil moisture, yield and other alfalfa grow characteristics during a two-year in situ observation study, and provide information on the best irrigation techniques and the water-use efficiency of alfalfa in the Agro-pastoral ecotone Northwestern China. The results showed that: the ARE, nRMSE and R² values of alfalfa soil water content, leaf area index and yield varied between 3.82% and 5.57%, 4.81% and 8.06%, and 0.86 and 0.93 respectively, and the accuracy of the calibrated and validated parameters was acceptable, and the model could be applied to this study. The water consumption of alfalfa ranged from 395.6 mm to 421.8 mm during the whole year, and the critical water consumption period was the branching stage and the bud stage. During the branching stage and the bud stage, water consumption was 30-31% and 31-33% of the total water consumption and the water consumption intensity averaging 2.97-3.04 mm/d and 4.23-4.97 mm/d. The variations of WUE and IWUE were 11.74-14.39 kg·m^-3 and 7.12-9.31 kg·m^-3. Irrigation increased the water productivity of rain fed alfalfa by 49.48-64.70%, and increased the yield of alfalfa by 17.87-34.72%. With the highest yield as the goal, the recommended irrigation volumes for normal and dry flow years were 200 mm and 240 mm; with the goal of the highest utilization of groundwater resources, the recommended irrigation volumes for normal and dry flow years were 160 mm and 192 mm. The results of this study are expected to provide scientific and technological support for the rational utilization of groundwater and scientific improvement of alfalfa yield in the Agro-pastoral ecotone Northwestern China.

Point 2: Define the abbreviation (lWUE) here and use it throughout the paper where appropriate.

Response 2: Thank you very much for the reviewer's opinion. Modifications have been made in the text.

Point 3: You may need to add at least 2 or more references here.

Response 3: Thank you very much for the reviewer's opinion. We will take this issue very seriously and make serious changes. We think your opinion is valuable, your opinion will be very helpful in improving the quality of our article! The following changes were made:

Three related documents were added, numbered 13-15.

13. JIA, Z.; OU, C.; SUN, S. Optimizing drip irrigation managements to improve alfalfa seed yield in semiarid region[J]. Agricultural Water Management, 2024, 297: 108830.

14. Mazahrih, N.; Albalawneh, A.; Bani Hani, N. Impact of reclaimed wastewater on alfalfa production under different irrigation methods[J]. Water Practice & Technology, 2024, 19(6): 2226-2236.

15. Dey, S.; Jha, G.; Min, D. Precision Irrigation Technologies for Water‐Wise and Climate Resilient Alfalfa Production[J]. Crops & Soils, 2024, 57(4): 4-11.

Point 4: Use the abbreviation after defining it and ensure consistency throughout the paper.

Response 4: Thank you very much for the reviewer's opinion.The text has been modified to define the abbreviations.

Modify as follows: water use efficiency (WUE).

Point 5: Define the abbreviation here.

Response 5: Thank you very much for the reviewer's opinion.The text has been modified to define the abbreviations.

Modify as follows: DSSAT (Decision Support System for Agrotechnology Transfer) .

Point 6: It is better to indicate how many soil moisture monitoring devices were installed and their spacing.

Response 6: Thank you very much for the reviewer's opinion. We will take this issue very seriously and make serious changes. We think your opinion is valuable, your opinion will be very helpful in improving the quality of our article! The following changes were made:

In each crop area, soil moisture monitoring equipment (9 devices are installed, with an interval of 100 meters) was installed to track soil moisture dynamics. The sensors were buried at depths of 10, 20, 30, 40, 50, 60, 70, 80, 90, and 100 cm, with data collected every hour.

Point 7: I recommend using the same terms here as in Table 2.

Response 7: Thank you very much for the reviewer's opinion. We will take this issue very seriously and make serious changes. We think your opinion is valuable, your opinion will be very helpful in improving the quality of our article! The following changes were made:

The growth period of alfalfa, from planting to harvest, is divided into two harvest stages and four growth stages: greening–branching, branching–budding, budding–blooming, and blossom–harvest.

Point 8: Pls. check the definition.

Response 8: Thank you very much for the reviewer's opinion.The text has been modified to ensure consistent definitions throughout the text.

Point 9: You may consider using of abbreviation after defining it.

Response 9: Thank you very much for the reviewer's opinion.The article has been modified.

Point 10: Please check this abbreviation.

Response 10: Thank you very much for the reviewer's opinion. The article has been modified.

Point 11: LAl- Leaf area index.

Response 11: Thank you very much for the reviewer's opinion. The article has been modified.

Response to Reviewer 4 Comments

1. Summary

Dear Reviewers:

Thank you for taking time out of your busy schedule to review the manuscript. Now we have carefully corrected and replied to the manuscript for this revision. The revision instructions are as follows:

Point 1: In what way were the growth indicators of the irrigation rate of alfalfa (from planting to harvesting) calculated and which parameters were taken into account?

Response 1: Thank you very much for the reviewer's opinion. The growth indicators for the irrigation rate of alfalfa, from planting to harvesting, were calculated by monitoring key parameters such as soil moisture content, plant height, leaf area index (LAI), and biomass yield throughout the growing season. Irrigation rates were adjusted based on real-time data from soil moisture sensors and weather data to optimize water use efficiency. The irrigation amount was updated periodically to ensure the plants received adequate moisture while avoiding water stress or excess.

Point 2: Was its infiltration rate taken into account when analyzing the soil? In what order?

Response 2: Thank you very much for the reviewer's opinion. Yes, the infiltration rate was considered during soil analysis. The infiltration rate was measured at various depths and stages of the alfalfa growing cycle using a infiltrometer. This data was integrated into the soil water balance model to determine the rate of water movement through the soil profile. The infiltration rate was particularly important in assessing the soil’s ability to absorb and retain irrigation water, helping to optimize irrigation schedules. The analysis was conducted in the following sequence: (1) initial soil permeability and infiltration rate measurements, (2) soil moisture monitoring. 

Point 3:What is the percentage of reliability of the DSSAT model you used?

Response 3: Thank you very much for the reviewer's opinion. The reliability of the DSSAT (Decision Support System for Agrotechnology Transfer) model used in this study was assessed through calibration and validation processes. The model's performance was tested by comparing its predicted results against field observations, including biomass yield and growth rates of alfalfa under varying irrigation regimes. Based on the calibration and validation tests, the model demonstrated a high degree of reliability with a prediction accuracy of approximately 85-90%. The reliability percentage was calculated by comparing observed and predicted values using statistical measures such as the root mean square error (RMSE) and the coefficient of determination (R²).